Random Time Changes in Quantitative Finance


Rafael Mendoza-Arriaga
UT Austin

Wednesday, March 5, 2014
4:15 - 5:15 PM


Abstract:

Subjecting a stochastic process to a random time change is a classical technique in stochastic analysis. In this talk we survey our recent work on using random time changes as a flexible model-building tool for designing stochastic processes that possess rich features required for empirical realism in financial modeling. These features include state-dependent and time-inhomogeneous jumps and stochastic volatility. Moreover, our modeling framework offers analytical and computational tractability which are required for operational purposes. We sketch applications across credit, commodity, equity, power generation systems and insurance.

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Operations Research Colloquia: http://or.stanford.edu/oras_seminars.html